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The demand for Big Data is increasing day by day. The [course_title] course illustrates the essential skills of Big Data including the JS application.

The course explains how digital technologies work. You will learn to enhance your coding skills through engaging and collaborative assignments. The basic concepts of algorithms, programming concepts such as data selection, iteration and functional decomposition, data abstraction and organisation will be focused on the course.

Apart from these, the course teaches you how to perform simple data visualisations using Processing JS.

Shortly, the course evaluates your knowledge and skills in solving small-scale data science problems working with real-world datasets.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

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  • Show it to prove your success


Course Credit: University of Adelaide

Course Curriculum

Welcome to Programming for Data Science 00:03:00
Introduction to the ProgramX Workspace 00:03:00
Module 1: Creative Code - Computational Thinking
Section 1: Introduction 00:01:00
What Does Code Mean For You? 00:03:00
Getting Into The Detail 00:04:00
What is Data Science? 00:03:00
Algorithms For Drawing Multiple Shapes 00:03:00
Order Is Important 00:04:00
Introducing Colour With Code 00:05:00
A Closer Look 00:02:00
Module 2: Building Blocks - Breaking It Down And Building It Up
Section 2: Introduction 00:02:00
Manipulating Shape Attributes Using Variables 00:03:00
More Manipulation 00:03:00
Weights And Shapes 00:01:00
Variables and Expressions 00:04:00
Continuing Our Example of Expressions 00:04:00
Let’s Take A Second To Review 00:02:00
Smarter Code – More Useful Variables 00:03:00
Smarter Coding Extended 00:04:00
Exploring Data 00:04:00
Module 3: Repetition: Creating and recognising patterns
Section 3: Introduction 00:04:00
Introduction to Repetition 00:04:00
Repetition in Processing 00:06:00
A Further Example 00:04:00
Combining Data and Repetition 00:03:00
More Loops 00:04:00
Loop-de-loop 00:04:00
More For Loops and Nesting 00:02:00
Nested Loops Yee Ha! 00:05:00
Module 4: Choice - Which Path To Follow?
Section 4: Introduction 00:05:00
Making Choices 00:03:00
More Complicated Choices 00:03:00
The Four Petals 00:03:00
Decision Making 00:02:00
More Decisions 00:05:00
Decisions, Decisions 00:03:00
And More Decisions 00:04:00
Using What We Know 00:05:00
Module 5: Repetition - Going Further
Section 5: Introduction 00:02:00
Creative Repetition 00:03:00
Building Patterns 00:03:00
The Frog Invasion 00:04:00
Frogs Galore! 00:02:00
While Loops 00:03:00
Taking Our Shapes Further! 00:04:00
Creating Curves! 00:02:00
Translating, Rotating And Scaling! 00:03:00
Module 6: Section 6: Testing and Debugging
Section 6: Introduction 00:01:00
Introduction to Testing 00:03:00
Further Testing 00:03:00
When Code goes Wrong 00:02:00
Debugging Code 00:04:00
Style is Everything 00:04:00
Styling our Code 00:03:00
Module 7: Arranging Our Data
Section 7: Introduction 00:03:00
What are Data Structures? 00:03:00
Static Arrays 00:05:00
Using our Arrays 00:03:00
Weather Reporting (Activity 18) 00:02:00
Dynamic Arrays 00:05:00
Using Dynamic Arrays 00:04:00
Module 8:
Section 8: Introduction 00:03:00
Introduction to Functions 00:03:00
Building and Using Functions 00:04:00
Decomposing Problems 00:02:00
Using Decomposition 00:04:00
Practice with Functions 00:04:00
Module 9: Data Science in Practice
Section 9: Introduction 00:02:00
Data Visualisation 00:02:00
Data Analysis 00:02:00
Analysis and Visualisation 00:02:00
Module 10: Where Next?
Section 10: Introduction 00:01:00
What we’ve done 00:03:00
Future Learning 00:01:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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